Repository logo
 

Navigating Mixed Traffic: Current State and Future Challenges in Integrating Autonomous and Human-Driven Vehicles

Accepted version
Peer-reviewed

Type

Conference Object

Change log

Authors

Chu, Kai-Fung 
Fan, Chenchen 
Iida, Fumiya 

Abstract

As autonomous vehicles (AVs) become increasingly prevalent in our society, it is crucial to address the technical challenges coexisting with human-driven vehicles (HVs) on the roads. Transportation administrators and constructors must be poised to harness the controllability and potential offered by these innovative vehicles when they gradually penetrate the roads in the near future. However, existing studies often focus on either the safe autonomous driving technology of single AVs alongside HVs or on collective coordination among AVs exclusively, neglecting the challenges inherent in heterogeneous multi-agent transportation systems. These challenges encompass critical aspects such as safety, human-robot interactions, and infrastructure adaptation, which Requires detailed exploration. This paper aims to explore the current state and future challenges in mixed traffic scenarios that lie at the intersection of artificial intelligence, multi-agent systems, safe control, and intelligent systems design in the context of advancing AV technology while ensuring safety and effective interaction between human, robot, and road infrastructure. We examine the current state-of-the-art of AV technology, identify key challenges for integrating human-centric approaches into the design, development, and deployment of AVs. Drawing upon insights from safety standards, human-robot interaction, and road infrastructure design frameworks, we highlight the important aspects surrounding AV and HV designs to enhance user trust, acceptance, and overall societal impact.

Description

Keywords

Journal Title

Conference Name

2024 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO)

Journal ISSN

Volume Title

Publisher

Publisher DOI

Publisher URL

Sponsorship
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 101034337.